aim-uofa / LoRAPruneLinks
☆63Updated last year
Alternatives and similar repositories for LoRAPrune
Users that are interested in LoRAPrune are comparing it to the libraries listed below
Sorting:
- [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference☆46Updated last year
- Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…☆50Updated last year
- [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…☆67Updated last year
- ☆23Updated last year
- ☆56Updated last year
- [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models☆68Updated 2 years ago
- ☆63Updated 2 years ago
- [EMNLP 2023, Main Conference] Sparse Low-rank Adaptation of Pre-trained Language Models☆84Updated last year
- LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning☆36Updated last year
- Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)☆67Updated 10 months ago
- Activation-aware Singular Value Decomposition for Compressing Large Language Models☆84Updated last year
- Awesome-Low-Rank-Adaptation☆127Updated last year
- Official Pytorch Implementation of "Outlier-weighed Layerwise Sampling for LLM Fine-tuning" by Pengxiang Li, Lu Yin, Xiaowei Gao, Shiwei …☆35Updated 7 months ago
- [NeurIPS 2024 Spotlight] EMR-Merging: Tuning-Free High-Performance Model Merging☆76Updated 10 months ago
- A block pruning framework for LLMs.☆27Updated 8 months ago
- Awesome LLM pruning papers all-in-one repository with integrating all useful resources and insights.☆146Updated 5 months ago
- A curated list of Model Merging methods.☆96Updated last month
- [ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers☆105Updated last year
- [ICML‘24] Official code for the paper "Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark ".☆124Updated 6 months ago
- ThinK: Thinner Key Cache by Query-Driven Pruning☆27Updated 11 months ago
- Code accompanying the paper "Massive Activations in Large Language Models"☆195Updated last year
- [ICLR‘24 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"☆103Updated 7 months ago
- A generalized framework for subspace tuning methods in parameter efficient fine-tuning.☆168Updated 7 months ago
- [ACL 2024] Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models☆113Updated last year
- [ICLR 2025] Official implementation of paper "Dynamic Low-Rank Sparse Adaptation for Large Language Models".☆23Updated 10 months ago
- This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).☆46Updated 3 years ago
- ☆43Updated last year
- Compressed LLMs for Efficient Text Generation [ICLR'24 Workshop]☆89Updated last year
- Official implementation of the ICLR paper "Streamlining Redundant Layers to Compress Large Language Models"☆38Updated 8 months ago
- [NeurIPS 2024] AlphaPruning: Using Heavy-Tailed Self Regularization Theory for Improved Layer-wise Pruning of Large Language Models☆31Updated 7 months ago